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pcuenq/pokemon-lora
pokemon-lora is a text-to-image model from pcuenq. Use it when you need an image from a text prompt. It is set up for diffusers. The card lists the license as creativeml-openrail-m.
These are LoRA adaption weights trained on base model https://huggingface.co/runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset.
Downloads · 30 days
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From the Hugging Face model README
These are LoRA adaption weights trained on base model https://huggingface.co/runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the lambdalabs/pokemon-blip-captions dataset.
The script below loads the base model, then applies the LoRA weights and performs inference:
import torch
from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
from huggingface_hub import model_info
# LoRA weights ~3 MB
model_path = "pcuenq/pokemon-lora"
info = model_info(model_path)
model_base = info.cardData["base_model"]
pipe = StableDiffusionPipeline.from_pretrained(model_base, torch_dtype=torch.float16)
pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)
pipe.unet.load_attn_procs(model_path)
pipe.to("cuda")
image = pipe("Green pokemon with menacing face", num_inference_steps=25).images[0]
image.save("green_pokemon.png")
Please, check our blog post or documentation for more details.
